{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分省固定资产投资完成额_累计增长指数和工业增加值_同比增长(%)指数月度数据分析与对比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>2019年8月</th>\n",
       "      <th>2019年7月</th>\n",
       "      <th>2019年6月</th>\n",
       "      <th>2019年5月</th>\n",
       "      <th>2019年4月</th>\n",
       "      <th>2019年3月</th>\n",
       "      <th>2018年12月</th>\n",
       "      <th>2018年11月</th>\n",
       "      <th>2018年10月</th>\n",
       "      <th>2018年9月</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>北京</td>\n",
       "      <td>160.5</td>\n",
       "      <td>105.2</td>\n",
       "      <td>104.7</td>\n",
       "      <td>105.8</td>\n",
       "      <td>109.4</td>\n",
       "      <td>106.9</td>\n",
       "      <td>84.5</td>\n",
       "      <td>83.6</td>\n",
       "      <td>83.0</td>\n",
       "      <td>83.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>天津</td>\n",
       "      <td>140.8</td>\n",
       "      <td>105.1</td>\n",
       "      <td>107.4</td>\n",
       "      <td>107.8</td>\n",
       "      <td>114.0</td>\n",
       "      <td>116.1</td>\n",
       "      <td>84.4</td>\n",
       "      <td>83.4</td>\n",
       "      <td>80.6</td>\n",
       "      <td>75.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>河北</td>\n",
       "      <td>94.2</td>\n",
       "      <td>95.3</td>\n",
       "      <td>95.6</td>\n",
       "      <td>94.8</td>\n",
       "      <td>94.9</td>\n",
       "      <td>95.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>95.9</td>\n",
       "      <td>95.9</td>\n",
       "      <td>95.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>山西</td>\n",
       "      <td>96.5</td>\n",
       "      <td>97.2</td>\n",
       "      <td>98.2</td>\n",
       "      <td>94.5</td>\n",
       "      <td>95.6</td>\n",
       "      <td>102.2</td>\n",
       "      <td>95.7</td>\n",
       "      <td>94.2</td>\n",
       "      <td>92.1</td>\n",
       "      <td>88.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>内蒙古</td>\n",
       "      <td>91.2</td>\n",
       "      <td>89.3</td>\n",
       "      <td>89.7</td>\n",
       "      <td>82.0</td>\n",
       "      <td>83.9</td>\n",
       "      <td>94.4</td>\n",
       "      <td>61.7</td>\n",
       "      <td>61.0</td>\n",
       "      <td>59.7</td>\n",
       "      <td>57.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>辽宁</td>\n",
       "      <td>86.9</td>\n",
       "      <td>86.1</td>\n",
       "      <td>84.8</td>\n",
       "      <td>82.3</td>\n",
       "      <td>84.6</td>\n",
       "      <td>93.2</td>\n",
       "      <td>93.7</td>\n",
       "      <td>93.3</td>\n",
       "      <td>93.7</td>\n",
       "      <td>94.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>吉林</td>\n",
       "      <td>79.6</td>\n",
       "      <td>83.0</td>\n",
       "      <td>84.9</td>\n",
       "      <td>77.2</td>\n",
       "      <td>77.8</td>\n",
       "      <td>90.8</td>\n",
       "      <td>91.6</td>\n",
       "      <td>91.2</td>\n",
       "      <td>90.6</td>\n",
       "      <td>90.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>黑龙江</td>\n",
       "      <td>90.8</td>\n",
       "      <td>91.7</td>\n",
       "      <td>93.5</td>\n",
       "      <td>92.0</td>\n",
       "      <td>88.2</td>\n",
       "      <td>94.2</td>\n",
       "      <td>85.3</td>\n",
       "      <td>85.4</td>\n",
       "      <td>85.7</td>\n",
       "      <td>86.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>上海</td>\n",
       "      <td>94.8</td>\n",
       "      <td>94.8</td>\n",
       "      <td>95.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>95.7</td>\n",
       "      <td>95.0</td>\n",
       "      <td>95.2</td>\n",
       "      <td>95.4</td>\n",
       "      <td>96.0</td>\n",
       "      <td>96.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>江苏</td>\n",
       "      <td>94.5</td>\n",
       "      <td>94.2</td>\n",
       "      <td>94.1</td>\n",
       "      <td>93.7</td>\n",
       "      <td>92.4</td>\n",
       "      <td>91.6</td>\n",
       "      <td>95.5</td>\n",
       "      <td>95.6</td>\n",
       "      <td>95.6</td>\n",
       "      <td>95.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>浙江</td>\n",
       "      <td>99.8</td>\n",
       "      <td>99.8</td>\n",
       "      <td>99.7</td>\n",
       "      <td>99.5</td>\n",
       "      <td>99.2</td>\n",
       "      <td>99.0</td>\n",
       "      <td>97.1</td>\n",
       "      <td>97.1</td>\n",
       "      <td>97.1</td>\n",
       "      <td>96.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>安徽</td>\n",
       "      <td>97.4</td>\n",
       "      <td>98.6</td>\n",
       "      <td>98.5</td>\n",
       "      <td>98.4</td>\n",
       "      <td>98.2</td>\n",
       "      <td>98.1</td>\n",
       "      <td>101.8</td>\n",
       "      <td>102.2</td>\n",
       "      <td>102.1</td>\n",
       "      <td>101.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>福建</td>\n",
       "      <td>97.0</td>\n",
       "      <td>96.9</td>\n",
       "      <td>97.0</td>\n",
       "      <td>96.6</td>\n",
       "      <td>97.0</td>\n",
       "      <td>98.3</td>\n",
       "      <td>101.5</td>\n",
       "      <td>101.8</td>\n",
       "      <td>102.6</td>\n",
       "      <td>103.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>江西</td>\n",
       "      <td>99.4</td>\n",
       "      <td>99.3</td>\n",
       "      <td>99.1</td>\n",
       "      <td>98.9</td>\n",
       "      <td>98.4</td>\n",
       "      <td>100.3</td>\n",
       "      <td>101.1</td>\n",
       "      <td>101.2</td>\n",
       "      <td>101.4</td>\n",
       "      <td>101.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>山东</td>\n",
       "      <td>80.6</td>\n",
       "      <td>83.4</td>\n",
       "      <td>83.3</td>\n",
       "      <td>83.0</td>\n",
       "      <td>82.5</td>\n",
       "      <td>84.6</td>\n",
       "      <td>94.1</td>\n",
       "      <td>95.0</td>\n",
       "      <td>95.5</td>\n",
       "      <td>95.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>河南</td>\n",
       "      <td>98.3</td>\n",
       "      <td>98.3</td>\n",
       "      <td>98.2</td>\n",
       "      <td>98.1</td>\n",
       "      <td>98.4</td>\n",
       "      <td>98.4</td>\n",
       "      <td>98.1</td>\n",
       "      <td>98.2</td>\n",
       "      <td>98.2</td>\n",
       "      <td>98.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>湖北</td>\n",
       "      <td>100.6</td>\n",
       "      <td>100.7</td>\n",
       "      <td>100.8</td>\n",
       "      <td>100.7</td>\n",
       "      <td>100.7</td>\n",
       "      <td>100.5</td>\n",
       "      <td>101.0</td>\n",
       "      <td>100.9</td>\n",
       "      <td>100.9</td>\n",
       "      <td>100.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>湖南</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>99.9</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>广东</td>\n",
       "      <td>100.8</td>\n",
       "      <td>100.8</td>\n",
       "      <td>100.5</td>\n",
       "      <td>100.7</td>\n",
       "      <td>101.0</td>\n",
       "      <td>101.2</td>\n",
       "      <td>100.7</td>\n",
       "      <td>100.4</td>\n",
       "      <td>100.2</td>\n",
       "      <td>100.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>广西</td>\n",
       "      <td>98.4</td>\n",
       "      <td>98.8</td>\n",
       "      <td>98.6</td>\n",
       "      <td>97.9</td>\n",
       "      <td>95.7</td>\n",
       "      <td>94.3</td>\n",
       "      <td>100.8</td>\n",
       "      <td>100.6</td>\n",
       "      <td>101.0</td>\n",
       "      <td>101.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>海南</td>\n",
       "      <td>69.7</td>\n",
       "      <td>68.1</td>\n",
       "      <td>67.0</td>\n",
       "      <td>61.7</td>\n",
       "      <td>58.0</td>\n",
       "      <td>57.5</td>\n",
       "      <td>77.5</td>\n",
       "      <td>76.2</td>\n",
       "      <td>75.3</td>\n",
       "      <td>76.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>重庆</td>\n",
       "      <td>95.1</td>\n",
       "      <td>95.6</td>\n",
       "      <td>96.1</td>\n",
       "      <td>96.0</td>\n",
       "      <td>96.4</td>\n",
       "      <td>96.6</td>\n",
       "      <td>97.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>97.5</td>\n",
       "      <td>97.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>四川</td>\n",
       "      <td>98.8</td>\n",
       "      <td>98.6</td>\n",
       "      <td>98.4</td>\n",
       "      <td>98.3</td>\n",
       "      <td>98.5</td>\n",
       "      <td>97.6</td>\n",
       "      <td>100.2</td>\n",
       "      <td>100.3</td>\n",
       "      <td>100.4</td>\n",
       "      <td>100.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>贵州</td>\n",
       "      <td>96.4</td>\n",
       "      <td>101.8</td>\n",
       "      <td>102.3</td>\n",
       "      <td>102.8</td>\n",
       "      <td>103.5</td>\n",
       "      <td>103.6</td>\n",
       "      <td>105.8</td>\n",
       "      <td>106.0</td>\n",
       "      <td>106.1</td>\n",
       "      <td>106.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>云南</td>\n",
       "      <td>101.2</td>\n",
       "      <td>97.4</td>\n",
       "      <td>99.1</td>\n",
       "      <td>95.8</td>\n",
       "      <td>95.8</td>\n",
       "      <td>101.4</td>\n",
       "      <td>101.6</td>\n",
       "      <td>101.0</td>\n",
       "      <td>100.4</td>\n",
       "      <td>100.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>西藏</td>\n",
       "      <td>65.3</td>\n",
       "      <td>66.2</td>\n",
       "      <td>63.7</td>\n",
       "      <td>66.1</td>\n",
       "      <td>59.0</td>\n",
       "      <td>60.2</td>\n",
       "      <td>99.8</td>\n",
       "      <td>100.2</td>\n",
       "      <td>95.7</td>\n",
       "      <td>99.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>陕西</td>\n",
       "      <td>90.7</td>\n",
       "      <td>91.6</td>\n",
       "      <td>92.5</td>\n",
       "      <td>93.7</td>\n",
       "      <td>97.7</td>\n",
       "      <td>99.2</td>\n",
       "      <td>100.4</td>\n",
       "      <td>100.4</td>\n",
       "      <td>100.9</td>\n",
       "      <td>101.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>甘肃</td>\n",
       "      <td>93.6</td>\n",
       "      <td>92.7</td>\n",
       "      <td>92.4</td>\n",
       "      <td>94.1</td>\n",
       "      <td>94.3</td>\n",
       "      <td>97.5</td>\n",
       "      <td>86.1</td>\n",
       "      <td>85.0</td>\n",
       "      <td>84.9</td>\n",
       "      <td>83.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>青海</td>\n",
       "      <td>79.4</td>\n",
       "      <td>81.7</td>\n",
       "      <td>80.1</td>\n",
       "      <td>72.6</td>\n",
       "      <td>73.8</td>\n",
       "      <td>96.5</td>\n",
       "      <td>97.3</td>\n",
       "      <td>97.1</td>\n",
       "      <td>97.0</td>\n",
       "      <td>94.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>宁夏</td>\n",
       "      <td>76.4</td>\n",
       "      <td>75.9</td>\n",
       "      <td>74.8</td>\n",
       "      <td>72.7</td>\n",
       "      <td>74.3</td>\n",
       "      <td>82.6</td>\n",
       "      <td>71.8</td>\n",
       "      <td>72.3</td>\n",
       "      <td>71.9</td>\n",
       "      <td>70.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>新疆</td>\n",
       "      <td>95.6</td>\n",
       "      <td>96.0</td>\n",
       "      <td>97.3</td>\n",
       "      <td>99.6</td>\n",
       "      <td>94.3</td>\n",
       "      <td>80.9</td>\n",
       "      <td>64.8</td>\n",
       "      <td>60.6</td>\n",
       "      <td>54.3</td>\n",
       "      <td>47.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     地区  2019年8月  2019年7月  2019年6月  2019年5月  2019年4月  2019年3月  2018年12月  \\\n",
       "0    北京    160.5    105.2    104.7    105.8    109.4    106.9      84.5   \n",
       "1    天津    140.8    105.1    107.4    107.8    114.0    116.1      84.4   \n",
       "2    河北     94.2     95.3     95.6     94.8     94.9     95.0      96.0   \n",
       "3    山西     96.5     97.2     98.2     94.5     95.6    102.2      95.7   \n",
       "4   内蒙古     91.2     89.3     89.7     82.0     83.9     94.4      61.7   \n",
       "5    辽宁     86.9     86.1     84.8     82.3     84.6     93.2      93.7   \n",
       "6    吉林     79.6     83.0     84.9     77.2     77.8     90.8      91.6   \n",
       "7   黑龙江     90.8     91.7     93.5     92.0     88.2     94.2      85.3   \n",
       "8    上海     94.8     94.8     95.0     95.0     95.7     95.0      95.2   \n",
       "9    江苏     94.5     94.2     94.1     93.7     92.4     91.6      95.5   \n",
       "10   浙江     99.8     99.8     99.7     99.5     99.2     99.0      97.1   \n",
       "11   安徽     97.4     98.6     98.5     98.4     98.2     98.1     101.8   \n",
       "12   福建     97.0     96.9     97.0     96.6     97.0     98.3     101.5   \n",
       "13   江西     99.4     99.3     99.1     98.9     98.4    100.3     101.1   \n",
       "14   山东     80.6     83.4     83.3     83.0     82.5     84.6      94.1   \n",
       "15   河南     98.3     98.3     98.2     98.1     98.4     98.4      98.1   \n",
       "16   湖北    100.6    100.7    100.8    100.7    100.7    100.5     101.0   \n",
       "17   湖南    100.0    100.0    100.0     99.9    100.0    100.0     100.0   \n",
       "18   广东    100.8    100.8    100.5    100.7    101.0    101.2     100.7   \n",
       "19   广西     98.4     98.8     98.6     97.9     95.7     94.3     100.8   \n",
       "20   海南     69.7     68.1     67.0     61.7     58.0     57.5      77.5   \n",
       "21   重庆     95.1     95.6     96.1     96.0     96.4     96.6      97.0   \n",
       "22   四川     98.8     98.6     98.4     98.3     98.5     97.6     100.2   \n",
       "23   贵州     96.4    101.8    102.3    102.8    103.5    103.6     105.8   \n",
       "24   云南    101.2     97.4     99.1     95.8     95.8    101.4     101.6   \n",
       "25   西藏     65.3     66.2     63.7     66.1     59.0     60.2      99.8   \n",
       "26   陕西     90.7     91.6     92.5     93.7     97.7     99.2     100.4   \n",
       "27   甘肃     93.6     92.7     92.4     94.1     94.3     97.5      86.1   \n",
       "28   青海     79.4     81.7     80.1     72.6     73.8     96.5      97.3   \n",
       "29   宁夏     76.4     75.9     74.8     72.7     74.3     82.6      71.8   \n",
       "30   新疆     95.6     96.0     97.3     99.6     94.3     80.9      64.8   \n",
       "\n",
       "    2018年11月  2018年10月  2018年9月  \n",
       "0       83.6      83.0     83.3  \n",
       "1       83.4      80.6     75.8  \n",
       "2       95.9      95.9     95.9  \n",
       "3       94.2      92.1     88.4  \n",
       "4       61.0      59.7     57.3  \n",
       "5       93.3      93.7     94.8  \n",
       "6       91.2      90.6     90.9  \n",
       "7       85.4      85.7     86.3  \n",
       "8       95.4      96.0     96.9  \n",
       "9       95.6      95.6     95.6  \n",
       "10      97.1      97.1     96.9  \n",
       "11     102.2     102.1    101.9  \n",
       "12     101.8     102.6    103.2  \n",
       "13     101.2     101.4    101.3  \n",
       "14      95.0      95.5     95.8  \n",
       "15      98.2      98.2     98.3  \n",
       "16     100.9     100.9    100.9  \n",
       "17     100.0     100.1    100.0  \n",
       "18     100.4     100.2    100.2  \n",
       "19     100.6     101.0    101.2  \n",
       "20      76.2      75.3     76.9  \n",
       "21      97.0      97.5     97.2  \n",
       "22     100.3     100.4    100.6  \n",
       "23     106.0     106.1    106.3  \n",
       "24     101.0     100.4    100.4  \n",
       "25     100.2      95.7     99.4  \n",
       "26     100.4     100.9    101.0  \n",
       "27      85.0      84.9     83.9  \n",
       "28      97.1      97.0     94.3  \n",
       "29      72.3      71.9     70.9  \n",
       "30      60.6      54.3     47.1  "
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"固定资产投资完成额_累计增长(%).csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['北京', '天津', '河北', '山西', '内蒙古', '辽宁', '吉林', '黑龙江', '上海', '江苏', '浙江', '安徽', '福建', '江西', '山东', '河南', '湖北', '湖南', '广东', '广西', '海南', '重庆', '四川', '贵州', '云南', '西藏', '陕西', '甘肃', '青海', '宁夏', '新疆']\n"
     ]
    }
   ],
   "source": [
    "print(list(df.地区))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[106.9, 116.1, 95.0, 102.2, 94.4, 93.2, 90.8, 94.2, 95.0, 91.6, 99.0, 98.1, 98.3, 100.3, 84.6, 98.4, 100.5, 100.0, 101.2, 94.3, 57.5, 96.6, 97.6, 103.6, 101.4, 60.2, 99.2, 97.5, 96.5, 82.6, 80.9]\n"
     ]
    }
   ],
   "source": [
    "print(list(df['2019年3月']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<zip object at 0x119c3bd48>\n"
     ]
    }
   ],
   "source": [
    "分省固定资产 = zip (list(df.地区),list(df['2019年3月']))\n",
    "print(分省固定资产)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('北京', 106.9), ('天津', 116.1), ('河北', 95.0), ('山西', 102.2), ('内蒙古', 94.4), ('辽宁', 93.2), ('吉林', 90.8), ('黑龙江', 94.2), ('上海', 95.0), ('江苏', 91.6), ('浙江', 99.0), ('安徽', 98.1), ('福建', 98.3), ('江西', 100.3), ('山东', 84.6), ('河南', 98.4), ('湖北', 100.5), ('湖南', 100.0), ('广东', 101.2), ('广西', 94.3), ('海南', 57.5), ('重庆', 96.6), ('四川', 97.6), ('贵州', 103.6), ('云南', 101.4), ('西藏', 60.2), ('陕西', 99.2), ('甘肃', 97.5), ('青海', 96.5), ('宁夏', 82.6), ('新疆', 80.9)]\n"
     ]
    }
   ],
   "source": [
    "分省固定资产= list(zip(list(df.地区),list(df['2019年3月'])))\n",
    "print(分省固定资产)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min', 'china':'https://assets.pyecharts.org/assets/maps/china'\n",
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       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"a3a3a18c8e544cf7abfba792b4223476\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts', 'china'], function(echarts) {\n",
       "                var chart_a3a3a18c8e544cf7abfba792b4223476 = echarts.init(\n",
       "                    document.getElementById('a3a3a18c8e544cf7abfba792b4223476'), 'white', {renderer: 'canvas'});\n",
       "                var option_a3a3a18c8e544cf7abfba792b4223476 = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
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       "        \"#61a0a8\",\n",
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       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
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       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
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       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"map\",\n",
       "            \"name\": \"\\u5206\\u7701\\u56fa\\u5b9a\\u8d44\\u4ea7\",\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"mapType\": \"china\",\n",
       "            \"data\": [\n",
       "                {\n",
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       "                {\n",
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       "                },\n",
       "                {\n",
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       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5409\\u6797\",\n",
       "                    \"value\": 90.8\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u9ed1\\u9f99\\u6c5f\",\n",
       "                    \"value\": 94.2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u4e0a\\u6d77\",\n",
       "                    \"value\": 95.0\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6c5f\\u82cf\",\n",
       "                    \"value\": 91.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6d59\\u6c5f\",\n",
       "                    \"value\": 99.0\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5b89\\u5fbd\",\n",
       "                    \"value\": 98.1\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u798f\\u5efa\",\n",
       "                    \"value\": 98.3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6c5f\\u897f\",\n",
       "                    \"value\": 100.3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5c71\\u4e1c\",\n",
       "                    \"value\": 84.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6cb3\\u5357\",\n",
       "                    \"value\": 98.4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6e56\\u5317\",\n",
       "                    \"value\": 100.5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6e56\\u5357\",\n",
       "                    \"value\": 100.0\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5e7f\\u4e1c\",\n",
       "                    \"value\": 101.2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5e7f\\u897f\",\n",
       "                    \"value\": 94.3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6d77\\u5357\",\n",
       "                    \"value\": 57.5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u91cd\\u5e86\",\n",
       "                    \"value\": 96.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u56db\\u5ddd\",\n",
       "                    \"value\": 97.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u8d35\\u5dde\",\n",
       "                    \"value\": 103.6\n",
       "                },\n",
       "                {\n",
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       "                    \"value\": 101.4\n",
       "                },\n",
       "                {\n",
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       "                    \"value\": 60.2\n",
       "                },\n",
       "                {\n",
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       "                    \"value\": 99.2\n",
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       "                },\n",
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       "                },\n",
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       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u65b0\\u7586\",\n",
       "                    \"value\": 80.9\n",
       "                }\n",
       "            ],\n",
       "            \"roam\": true,\n",
       "            \"zoom\": 1,\n",
       "            \"showLegendSymbol\": true,\n",
       "            \"emphasis\": {}\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u5206\\u7701\\u56fa\\u5b9a\\u8d44\\u4ea7\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u5206\\u7701\\u56fa\\u5b9a\\u8d44\\u4ea7\": true\n",
       "            },\n",
       "            \"show\": true\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"2019\\u5e748\\u6708\\u4e2d\\u56fd\\u5206\\u7701\\u56fa\\u5b9a\\u8d44\\u4ea7\\u6295\\u8d44\\u5b8c\\u6210\\u989d_\\u7d2f\\u8ba1\\u589e\\u957f\\u6570\\u636e\"\n",
       "        }\n",
       "    ],\n",
       "    \"visualMap\": {\n",
       "        \"show\": true,\n",
       "        \"type\": \"piecewise\",\n",
       "        \"min\": 60,\n",
       "        \"max\": 120,\n",
       "        \"inRange\": {\n",
       "            \"color\": [\n",
       "                \"#50a3ba\",\n",
       "                \"#eac763\",\n",
       "                \"#d94e5d\"\n",
       "            ]\n",
       "        },\n",
       "        \"calculable\": true,\n",
       "        \"splitNumber\": 5,\n",
       "        \"orient\": \"vertical\",\n",
       "        \"showLabel\": true\n",
       "    }\n",
       "};\n",
       "                chart_a3a3a18c8e544cf7abfba792b4223476.setOption(option_a3a3a18c8e544cf7abfba792b4223476);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x119c3f898>"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "from pyecharts import options as opts\n",
    "from pyecharts.charts import Map\n",
    "\n",
    "\n",
    "def map_visualmap() -> Map:\n",
    "    c = (\n",
    "        Map()\n",
    "        .add(\"分省固定资产\", 分省固定资产, \"china\")\n",
    "        .set_global_opts(\n",
    "            title_opts=opts.TitleOpts(title=\"2019年8月中国分省固定资产投资完成额_累计增长数据\"),\n",
    "            visualmap_opts=opts.VisualMapOpts(max_=120,min_=60, is_piecewise=True),\n",
    "        )\n",
    "    )\n",
    "    return c\n",
    "\n",
    "map_visualmap().render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>地区</th>\n",
       "      <th>2019年8月</th>\n",
       "      <th>2019年7月</th>\n",
       "      <th>2019年6月</th>\n",
       "      <th>2019年5月</th>\n",
       "      <th>2019年4月</th>\n",
       "      <th>2019年3月</th>\n",
       "      <th>2018年12月</th>\n",
       "      <th>2018年11月</th>\n",
       "      <th>2018年10月</th>\n",
       "      <th>2018年9月</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>北京</td>\n",
       "      <td>101.7</td>\n",
       "      <td>101.6</td>\n",
       "      <td>97.9</td>\n",
       "      <td>100.4</td>\n",
       "      <td>101.4</td>\n",
       "      <td>115.1</td>\n",
       "      <td>97.2</td>\n",
       "      <td>96.4</td>\n",
       "      <td>100.5</td>\n",
       "      <td>101.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>天津</td>\n",
       "      <td>99.8</td>\n",
       "      <td>99.5</td>\n",
       "      <td>102.1</td>\n",
       "      <td>100.9</td>\n",
       "      <td>102.8</td>\n",
       "      <td>110.8</td>\n",
       "      <td>100.8</td>\n",
       "      <td>96.8</td>\n",
       "      <td>102.2</td>\n",
       "      <td>99.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>河北</td>\n",
       "      <td>103.9</td>\n",
       "      <td>105.2</td>\n",
       "      <td>110.4</td>\n",
       "      <td>106.6</td>\n",
       "      <td>105.3</td>\n",
       "      <td>111.6</td>\n",
       "      <td>108.1</td>\n",
       "      <td>109.2</td>\n",
       "      <td>110.2</td>\n",
       "      <td>107.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>山西</td>\n",
       "      <td>104.0</td>\n",
       "      <td>105.8</td>\n",
       "      <td>108.1</td>\n",
       "      <td>106.3</td>\n",
       "      <td>102.5</td>\n",
       "      <td>110.8</td>\n",
       "      <td>103.0</td>\n",
       "      <td>104.9</td>\n",
       "      <td>103.8</td>\n",
       "      <td>99.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>内蒙古</td>\n",
       "      <td>109.8</td>\n",
       "      <td>113.5</td>\n",
       "      <td>110.5</td>\n",
       "      <td>107.6</td>\n",
       "      <td>104.1</td>\n",
       "      <td>108.8</td>\n",
       "      <td>105.2</td>\n",
       "      <td>111.5</td>\n",
       "      <td>112.7</td>\n",
       "      <td>108.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>辽宁</td>\n",
       "      <td>102.6</td>\n",
       "      <td>105.2</td>\n",
       "      <td>106.9</td>\n",
       "      <td>101.4</td>\n",
       "      <td>103.0</td>\n",
       "      <td>110.3</td>\n",
       "      <td>110.4</td>\n",
       "      <td>108.3</td>\n",
       "      <td>111.8</td>\n",
       "      <td>108.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>吉林</td>\n",
       "      <td>105.3</td>\n",
       "      <td>99.8</td>\n",
       "      <td>96.5</td>\n",
       "      <td>98.1</td>\n",
       "      <td>96.0</td>\n",
       "      <td>103.5</td>\n",
       "      <td>104.3</td>\n",
       "      <td>94.5</td>\n",
       "      <td>99.9</td>\n",
       "      <td>104.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>黑龙江</td>\n",
       "      <td>101.3</td>\n",
       "      <td>100.3</td>\n",
       "      <td>106.3</td>\n",
       "      <td>96.9</td>\n",
       "      <td>97.0</td>\n",
       "      <td>107.7</td>\n",
       "      <td>104.4</td>\n",
       "      <td>104.7</td>\n",
       "      <td>102.8</td>\n",
       "      <td>95.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>上海</td>\n",
       "      <td>102.5</td>\n",
       "      <td>92.7</td>\n",
       "      <td>101.8</td>\n",
       "      <td>95.8</td>\n",
       "      <td>95.9</td>\n",
       "      <td>101.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>96.3</td>\n",
       "      <td>102.9</td>\n",
       "      <td>96.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>江苏</td>\n",
       "      <td>105.5</td>\n",
       "      <td>106.0</td>\n",
       "      <td>109.7</td>\n",
       "      <td>105.2</td>\n",
       "      <td>104.7</td>\n",
       "      <td>109.8</td>\n",
       "      <td>104.6</td>\n",
       "      <td>101.9</td>\n",
       "      <td>104.3</td>\n",
       "      <td>103.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>浙江</td>\n",
       "      <td>104.0</td>\n",
       "      <td>104.5</td>\n",
       "      <td>107.0</td>\n",
       "      <td>103.1</td>\n",
       "      <td>101.3</td>\n",
       "      <td>116.9</td>\n",
       "      <td>104.3</td>\n",
       "      <td>105.6</td>\n",
       "      <td>105.8</td>\n",
       "      <td>107.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>安徽</td>\n",
       "      <td>105.1</td>\n",
       "      <td>106.9</td>\n",
       "      <td>109.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>106.6</td>\n",
       "      <td>109.3</td>\n",
       "      <td>110.9</td>\n",
       "      <td>108.4</td>\n",
       "      <td>109.7</td>\n",
       "      <td>110.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>福建</td>\n",
       "      <td>109.2</td>\n",
       "      <td>108.2</td>\n",
       "      <td>108.8</td>\n",
       "      <td>107.3</td>\n",
       "      <td>109.0</td>\n",
       "      <td>109.1</td>\n",
       "      <td>109.5</td>\n",
       "      <td>108.7</td>\n",
       "      <td>109.6</td>\n",
       "      <td>109.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>江西</td>\n",
       "      <td>108.7</td>\n",
       "      <td>108.0</td>\n",
       "      <td>108.9</td>\n",
       "      <td>108.4</td>\n",
       "      <td>109.3</td>\n",
       "      <td>110.3</td>\n",
       "      <td>109.8</td>\n",
       "      <td>107.8</td>\n",
       "      <td>108.7</td>\n",
       "      <td>108.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>山东</td>\n",
       "      <td>95.5</td>\n",
       "      <td>98.3</td>\n",
       "      <td>101.4</td>\n",
       "      <td>99.6</td>\n",
       "      <td>98.5</td>\n",
       "      <td>105.6</td>\n",
       "      <td>104.3</td>\n",
       "      <td>104.6</td>\n",
       "      <td>104.8</td>\n",
       "      <td>106.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>河南</td>\n",
       "      <td>106.6</td>\n",
       "      <td>107.2</td>\n",
       "      <td>107.7</td>\n",
       "      <td>107.5</td>\n",
       "      <td>107.7</td>\n",
       "      <td>109.3</td>\n",
       "      <td>109.2</td>\n",
       "      <td>106.7</td>\n",
       "      <td>104.5</td>\n",
       "      <td>105.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>湖北</td>\n",
       "      <td>106.4</td>\n",
       "      <td>107.0</td>\n",
       "      <td>107.9</td>\n",
       "      <td>106.6</td>\n",
       "      <td>109.6</td>\n",
       "      <td>109.7</td>\n",
       "      <td>105.5</td>\n",
       "      <td>104.4</td>\n",
       "      <td>103.7</td>\n",
       "      <td>108.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>湖南</td>\n",
       "      <td>107.5</td>\n",
       "      <td>108.0</td>\n",
       "      <td>109.6</td>\n",
       "      <td>106.9</td>\n",
       "      <td>108.5</td>\n",
       "      <td>108.8</td>\n",
       "      <td>109.9</td>\n",
       "      <td>106.7</td>\n",
       "      <td>108.5</td>\n",
       "      <td>107.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>广东</td>\n",
       "      <td>100.6</td>\n",
       "      <td>101.9</td>\n",
       "      <td>104.7</td>\n",
       "      <td>103.8</td>\n",
       "      <td>101.1</td>\n",
       "      <td>111.7</td>\n",
       "      <td>107.3</td>\n",
       "      <td>106.2</td>\n",
       "      <td>107.5</td>\n",
       "      <td>104.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>广西</td>\n",
       "      <td>102.3</td>\n",
       "      <td>102.0</td>\n",
       "      <td>102.3</td>\n",
       "      <td>92.6</td>\n",
       "      <td>97.8</td>\n",
       "      <td>107.4</td>\n",
       "      <td>106.2</td>\n",
       "      <td>99.9</td>\n",
       "      <td>103.0</td>\n",
       "      <td>110.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>海南</td>\n",
       "      <td>98.3</td>\n",
       "      <td>101.5</td>\n",
       "      <td>94.9</td>\n",
       "      <td>101.7</td>\n",
       "      <td>102.9</td>\n",
       "      <td>105.9</td>\n",
       "      <td>122.5</td>\n",
       "      <td>116.2</td>\n",
       "      <td>106.3</td>\n",
       "      <td>100.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>重庆</td>\n",
       "      <td>106.4</td>\n",
       "      <td>105.5</td>\n",
       "      <td>106.0</td>\n",
       "      <td>106.6</td>\n",
       "      <td>104.2</td>\n",
       "      <td>106.4</td>\n",
       "      <td>99.3</td>\n",
       "      <td>95.0</td>\n",
       "      <td>97.5</td>\n",
       "      <td>101.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>四川</td>\n",
       "      <td>107.8</td>\n",
       "      <td>107.9</td>\n",
       "      <td>108.0</td>\n",
       "      <td>108.4</td>\n",
       "      <td>108.2</td>\n",
       "      <td>108.6</td>\n",
       "      <td>108.3</td>\n",
       "      <td>108.2</td>\n",
       "      <td>108.1</td>\n",
       "      <td>109.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>贵州</td>\n",
       "      <td>106.9</td>\n",
       "      <td>108.8</td>\n",
       "      <td>114.1</td>\n",
       "      <td>107.1</td>\n",
       "      <td>105.5</td>\n",
       "      <td>111.5</td>\n",
       "      <td>111.3</td>\n",
       "      <td>108.5</td>\n",
       "      <td>107.6</td>\n",
       "      <td>105.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>云南</td>\n",
       "      <td>106.6</td>\n",
       "      <td>107.8</td>\n",
       "      <td>110.1</td>\n",
       "      <td>112.6</td>\n",
       "      <td>107.2</td>\n",
       "      <td>110.4</td>\n",
       "      <td>108.0</td>\n",
       "      <td>106.2</td>\n",
       "      <td>114.2</td>\n",
       "      <td>109.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>西藏</td>\n",
       "      <td>104.5</td>\n",
       "      <td>115.3</td>\n",
       "      <td>103.8</td>\n",
       "      <td>109.4</td>\n",
       "      <td>104.2</td>\n",
       "      <td>107.2</td>\n",
       "      <td>110.4</td>\n",
       "      <td>108.9</td>\n",
       "      <td>101.9</td>\n",
       "      <td>115.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>陕西</td>\n",
       "      <td>99.8</td>\n",
       "      <td>105.0</td>\n",
       "      <td>109.3</td>\n",
       "      <td>99.8</td>\n",
       "      <td>99.7</td>\n",
       "      <td>104.2</td>\n",
       "      <td>109.5</td>\n",
       "      <td>107.2</td>\n",
       "      <td>111.8</td>\n",
       "      <td>107.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>甘肃</td>\n",
       "      <td>98.2</td>\n",
       "      <td>103.3</td>\n",
       "      <td>101.2</td>\n",
       "      <td>93.6</td>\n",
       "      <td>104.2</td>\n",
       "      <td>111.5</td>\n",
       "      <td>108.8</td>\n",
       "      <td>93.6</td>\n",
       "      <td>98.4</td>\n",
       "      <td>108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>青海</td>\n",
       "      <td>104.6</td>\n",
       "      <td>103.7</td>\n",
       "      <td>107.0</td>\n",
       "      <td>101.2</td>\n",
       "      <td>105.8</td>\n",
       "      <td>109.6</td>\n",
       "      <td>110.1</td>\n",
       "      <td>109.0</td>\n",
       "      <td>109.5</td>\n",
       "      <td>109.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>宁夏</td>\n",
       "      <td>109.2</td>\n",
       "      <td>114.9</td>\n",
       "      <td>105.8</td>\n",
       "      <td>107.1</td>\n",
       "      <td>101.3</td>\n",
       "      <td>102.4</td>\n",
       "      <td>115.5</td>\n",
       "      <td>107.8</td>\n",
       "      <td>113.0</td>\n",
       "      <td>114.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>新疆</td>\n",
       "      <td>106.2</td>\n",
       "      <td>107.5</td>\n",
       "      <td>105.0</td>\n",
       "      <td>104.1</td>\n",
       "      <td>105.2</td>\n",
       "      <td>102.3</td>\n",
       "      <td>111.9</td>\n",
       "      <td>110.0</td>\n",
       "      <td>103.9</td>\n",
       "      <td>101.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     地区  2019年8月  2019年7月  2019年6月  2019年5月  2019年4月  2019年3月  2018年12月  \\\n",
       "0    北京    101.7    101.6     97.9    100.4    101.4    115.1      97.2   \n",
       "1    天津     99.8     99.5    102.1    100.9    102.8    110.8     100.8   \n",
       "2    河北    103.9    105.2    110.4    106.6    105.3    111.6     108.1   \n",
       "3    山西    104.0    105.8    108.1    106.3    102.5    110.8     103.0   \n",
       "4   内蒙古    109.8    113.5    110.5    107.6    104.1    108.8     105.2   \n",
       "5    辽宁    102.6    105.2    106.9    101.4    103.0    110.3     110.4   \n",
       "6    吉林    105.3     99.8     96.5     98.1     96.0    103.5     104.3   \n",
       "7   黑龙江    101.3    100.3    106.3     96.9     97.0    107.7     104.4   \n",
       "8    上海    102.5     92.7    101.8     95.8     95.9    101.0      93.0   \n",
       "9    江苏    105.5    106.0    109.7    105.2    104.7    109.8     104.6   \n",
       "10   浙江    104.0    104.5    107.0    103.1    101.3    116.9     104.3   \n",
       "11   安徽    105.1    106.9    109.0    107.0    106.6    109.3     110.9   \n",
       "12   福建    109.2    108.2    108.8    107.3    109.0    109.1     109.5   \n",
       "13   江西    108.7    108.0    108.9    108.4    109.3    110.3     109.8   \n",
       "14   山东     95.5     98.3    101.4     99.6     98.5    105.6     104.3   \n",
       "15   河南    106.6    107.2    107.7    107.5    107.7    109.3     109.2   \n",
       "16   湖北    106.4    107.0    107.9    106.6    109.6    109.7     105.5   \n",
       "17   湖南    107.5    108.0    109.6    106.9    108.5    108.8     109.9   \n",
       "18   广东    100.6    101.9    104.7    103.8    101.1    111.7     107.3   \n",
       "19   广西    102.3    102.0    102.3     92.6     97.8    107.4     106.2   \n",
       "20   海南     98.3    101.5     94.9    101.7    102.9    105.9     122.5   \n",
       "21   重庆    106.4    105.5    106.0    106.6    104.2    106.4      99.3   \n",
       "22   四川    107.8    107.9    108.0    108.4    108.2    108.6     108.3   \n",
       "23   贵州    106.9    108.8    114.1    107.1    105.5    111.5     111.3   \n",
       "24   云南    106.6    107.8    110.1    112.6    107.2    110.4     108.0   \n",
       "25   西藏    104.5    115.3    103.8    109.4    104.2    107.2     110.4   \n",
       "26   陕西     99.8    105.0    109.3     99.8     99.7    104.2     109.5   \n",
       "27   甘肃     98.2    103.3    101.2     93.6    104.2    111.5     108.8   \n",
       "28   青海    104.6    103.7    107.0    101.2    105.8    109.6     110.1   \n",
       "29   宁夏    109.2    114.9    105.8    107.1    101.3    102.4     115.5   \n",
       "30   新疆    106.2    107.5    105.0    104.1    105.2    102.3     111.9   \n",
       "\n",
       "    2018年11月  2018年10月  2018年9月  \n",
       "0       96.4     100.5    101.1  \n",
       "1       96.8     102.2     99.9  \n",
       "2      109.2     110.2    107.7  \n",
       "3      104.9     103.8     99.2  \n",
       "4      111.5     112.7    108.9  \n",
       "5      108.3     111.8    108.5  \n",
       "6       94.5      99.9    104.5  \n",
       "7      104.7     102.8     95.6  \n",
       "8       96.3     102.9     96.1  \n",
       "9      101.9     104.3    103.4  \n",
       "10     105.6     105.8    107.6  \n",
       "11     108.4     109.7    110.4  \n",
       "12     108.7     109.6    109.6  \n",
       "13     107.8     108.7    108.3  \n",
       "14     104.6     104.8    106.4  \n",
       "15     106.7     104.5    105.3  \n",
       "16     104.4     103.7    108.1  \n",
       "17     106.7     108.5    107.2  \n",
       "18     106.2     107.5    104.3  \n",
       "19      99.9     103.0    110.4  \n",
       "20     116.2     106.3    100.9  \n",
       "21      95.0      97.5    101.5  \n",
       "22     108.2     108.1    109.0  \n",
       "23     108.5     107.6    105.5  \n",
       "24     106.2     114.2    109.5  \n",
       "25     108.9     101.9    115.9  \n",
       "26     107.2     111.8    107.1  \n",
       "27      93.6      98.4    108.0  \n",
       "28     109.0     109.5    109.1  \n",
       "29     107.8     113.0    114.6  \n",
       "30     110.0     103.9    101.6  "
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"工业增加值_同比增长(%).csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['北京', '天津', '河北', '山西', '内蒙古', '辽宁', '吉林', '黑龙江', '上海', '江苏', '浙江', '安徽', '福建', '江西', '山东', '河南', '湖北', '湖南', '广东', '广西', '海南', '重庆', '四川', '贵州', '云南', '西藏', '陕西', '甘肃', '青海', '宁夏', '新疆']\n"
     ]
    }
   ],
   "source": [
    "print(list(df.地区))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[101.7, 99.8, 103.9, 104.0, 109.8, 102.6, 105.3, 101.3, 102.5, 105.5, 104.0, 105.1, 109.2, 108.7, 95.5, 106.6, 106.4, 107.5, 100.6, 102.3, 98.3, 106.4, 107.8, 106.9, 106.6, 104.5, 99.8, 98.2, 104.6, 109.2, 106.2]\n"
     ]
    }
   ],
   "source": [
    "print(list(df['2019年8月']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<zip object at 0x119bdcdc8>\n"
     ]
    }
   ],
   "source": [
    "分省工业增加值 = zip (list(df.地区),list(df['2019年8月']))\n",
    "print(分省工业增加值)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('北京', 101.7), ('天津', 99.8), ('河北', 103.9), ('山西', 104.0), ('内蒙古', 109.8), ('辽宁', 102.6), ('吉林', 105.3), ('黑龙江', 101.3), ('上海', 102.5), ('江苏', 105.5), ('浙江', 104.0), ('安徽', 105.1), ('福建', 109.2), ('江西', 108.7), ('山东', 95.5), ('河南', 106.6), ('湖北', 106.4), ('湖南', 107.5), ('广东', 100.6), ('广西', 102.3), ('海南', 98.3), ('重庆', 106.4), ('四川', 107.8), ('贵州', 106.9), ('云南', 106.6), ('西藏', 104.5), ('陕西', 99.8), ('甘肃', 98.2), ('青海', 104.6), ('宁夏', 109.2), ('新疆', 106.2)]\n"
     ]
    }
   ],
   "source": [
    "分省工业增加值 = list(zip (list(df.地区),list(df['2019年8月'])))\n",
    "print(分省工业增加值)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
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       "        \"#61a0a8\",\n",
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       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
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       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
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       "    \"series\": [\n",
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       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"mapType\": \"china\",\n",
       "            \"data\": [\n",
       "                {\n",
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       "                },\n",
       "                {\n",
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       "                    \"value\": 99.8\n",
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       "                {\n",
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       "                    \"value\": 103.9\n",
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       "                {\n",
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       "                },\n",
       "                {\n",
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       "                    \"value\": 102.6\n",
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       "                {\n",
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       "                    \"value\": 101.3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u4e0a\\u6d77\",\n",
       "                    \"value\": 102.5\n",
       "                },\n",
       "                {\n",
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       "                    \"value\": 105.5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6d59\\u6c5f\",\n",
       "                    \"value\": 104.0\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5b89\\u5fbd\",\n",
       "                    \"value\": 105.1\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u798f\\u5efa\",\n",
       "                    \"value\": 109.2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6c5f\\u897f\",\n",
       "                    \"value\": 108.7\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5c71\\u4e1c\",\n",
       "                    \"value\": 95.5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6cb3\\u5357\",\n",
       "                    \"value\": 106.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6e56\\u5317\",\n",
       "                    \"value\": 106.4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6e56\\u5357\",\n",
       "                    \"value\": 107.5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5e7f\\u4e1c\",\n",
       "                    \"value\": 100.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5e7f\\u897f\",\n",
       "                    \"value\": 102.3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6d77\\u5357\",\n",
       "                    \"value\": 98.3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u91cd\\u5e86\",\n",
       "                    \"value\": 106.4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u56db\\u5ddd\",\n",
       "                    \"value\": 107.8\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u8d35\\u5dde\",\n",
       "                    \"value\": 106.9\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u4e91\\u5357\",\n",
       "                    \"value\": 106.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u897f\\u85cf\",\n",
       "                    \"value\": 104.5\n",
       "                },\n",
       "                {\n",
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       "                    \"value\": 99.8\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u7518\\u8083\",\n",
       "                    \"value\": 98.2\n",
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       "                {\n",
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       "                    \"value\": 104.6\n",
       "                },\n",
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       "                    \"value\": 109.2\n",
       "                },\n",
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       "            \"roam\": true,\n",
       "            \"zoom\": 1,\n",
       "            \"showLegendSymbol\": true,\n",
       "            \"emphasis\": {}\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u5206\\u7701\\u5de5\\u4e1a\\u589e\\u52a0\\u503c\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u5206\\u7701\\u5de5\\u4e1a\\u589e\\u52a0\\u503c\": true\n",
       "            },\n",
       "            \"show\": true\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"2019\\u5e748\\u6708\\u4e2d\\u56fd\\u5206\\u7701\\u5de5\\u4e1a\\u589e\\u52a0\\u503c_\\u540c\\u6bd4\\u589e\\u957f(%)\\u6570\\u636e\"\n",
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       "    \"visualMap\": {\n",
       "        \"show\": true,\n",
       "        \"type\": \"piecewise\",\n",
       "        \"min\": 60,\n",
       "        \"max\": 120,\n",
       "        \"inRange\": {\n",
       "            \"color\": [\n",
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       "                \"#eac763\",\n",
       "                \"#d94e5d\"\n",
       "            ]\n",
       "        },\n",
       "        \"calculable\": true,\n",
       "        \"splitNumber\": 5,\n",
       "        \"orient\": \"vertical\",\n",
       "        \"showLabel\": true\n",
       "    }\n",
       "};\n",
       "                chart_429479d7e46f4028a3949db2cc11f523.setOption(option_429479d7e46f4028a3949db2cc11f523);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x119c3f240>"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "def geo_工业增加值() -> Map:\n",
    "    c = (\n",
    "        Map()\n",
    "        .add(\"分省工业增加值\", 分省工业增加值, \"china\")\n",
    "        .set_global_opts(\n",
    "            title_opts=opts.TitleOpts(title=\"2019年8月中国分省工业增加值_同比增长(%)数据\"),\n",
    "            visualmap_opts=opts.VisualMapOpts(max_=120,min_=60, is_piecewise=True),\n",
    "        )\n",
    "    )\n",
    "    return c\n",
    "\n",
    "geo_工业增加值().render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
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       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min', 'china':'https://assets.pyecharts.org/assets/maps/china'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"97b2470b91994b48a9c9e66690a07e50\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts', 'china'], function(echarts) {\n",
       "                var chart_97b2470b91994b48a9c9e66690a07e50 = echarts.init(\n",
       "                    document.getElementById('97b2470b91994b48a9c9e66690a07e50'), 'white', {renderer: 'canvas'});\n",
       "                var option_97b2470b91994b48a9c9e66690a07e50 = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
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       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
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       "        \"#f47920\",\n",
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       "        \"#fab27b\",\n",
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       "        \"#6950a1\",\n",
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       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"map\",\n",
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       "            \"label\": {\n",
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       "                \"position\": \"top\",\n",
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       "            \"mapType\": \"china\",\n",
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       "                    \"value\": 101.7\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5929\\u6d25\",\n",
       "                    \"value\": 99.8\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6cb3\\u5317\",\n",
       "                    \"value\": 103.9\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5c71\\u897f\",\n",
       "                    \"value\": 104.0\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5185\\u8499\\u53e4\",\n",
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       "                    \"name\": \"\\u8fbd\\u5b81\",\n",
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       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5409\\u6797\",\n",
       "                    \"value\": 105.3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u9ed1\\u9f99\\u6c5f\",\n",
       "                    \"value\": 101.3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u4e0a\\u6d77\",\n",
       "                    \"value\": 102.5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6c5f\\u82cf\",\n",
       "                    \"value\": 105.5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6d59\\u6c5f\",\n",
       "                    \"value\": 104.0\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5b89\\u5fbd\",\n",
       "                    \"value\": 105.1\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u798f\\u5efa\",\n",
       "                    \"value\": 109.2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6c5f\\u897f\",\n",
       "                    \"value\": 108.7\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5c71\\u4e1c\",\n",
       "                    \"value\": 95.5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6cb3\\u5357\",\n",
       "                    \"value\": 106.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6e56\\u5317\",\n",
       "                    \"value\": 106.4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6e56\\u5357\",\n",
       "                    \"value\": 107.5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5e7f\\u4e1c\",\n",
       "                    \"value\": 100.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5e7f\\u897f\",\n",
       "                    \"value\": 102.3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6d77\\u5357\",\n",
       "                    \"value\": 98.3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u91cd\\u5e86\",\n",
       "                    \"value\": 106.4\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u56db\\u5ddd\",\n",
       "                    \"value\": 107.8\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u8d35\\u5dde\",\n",
       "                    \"value\": 106.9\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u4e91\\u5357\",\n",
       "                    \"value\": 106.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u897f\\u85cf\",\n",
       "                    \"value\": 104.5\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u9655\\u897f\",\n",
       "                    \"value\": 99.8\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u7518\\u8083\",\n",
       "                    \"value\": 98.2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u9752\\u6d77\",\n",
       "                    \"value\": 104.6\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5b81\\u590f\",\n",
       "                    \"value\": 109.2\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u65b0\\u7586\",\n",
       "                    \"value\": 106.2\n",
       "                }\n",
       "            ],\n",
       "            \"roam\": true,\n",
       "            \"zoom\": 1,\n",
       "            \"showLegendSymbol\": true,\n",
       "            \"emphasis\": {}\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u5206\\u7701\\u5de5\\u4e1a\\u589e\\u52a0\\u503c\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u5206\\u7701\\u5de5\\u4e1a\\u589e\\u52a0\\u503c\": true\n",
       "            },\n",
       "            \"show\": true\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"2019\\u5e748\\u6708\\u4e2d\\u56fd\\u5206\\u7701\\u5de5\\u4e1a\\u589e\\u52a0\\u503c_\\u540c\\u6bd4\\u589e\\u957f(%)\\u6570\\u636e\"\n",
       "        }\n",
       "    ],\n",
       "    \"visualMap\": {\n",
       "        \"show\": true,\n",
       "        \"type\": \"piecewise\",\n",
       "        \"min\": 60,\n",
       "        \"max\": 120,\n",
       "        \"inRange\": {\n",
       "            \"color\": [\n",
       "                \"#50a3ba\",\n",
       "                \"#eac763\",\n",
       "                \"#d94e5d\"\n",
       "            ]\n",
       "        },\n",
       "        \"calculable\": true,\n",
       "        \"splitNumber\": 5,\n",
       "        \"orient\": \"vertical\",\n",
       "        \"showLabel\": true\n",
       "    }\n",
       "};\n",
       "                chart_97b2470b91994b48a9c9e66690a07e50.setOption(option_97b2470b91994b48a9c9e66690a07e50);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x119bdec50>"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_工业增加值().render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分省固定资产投资完成额累计增长指数和工业增加值同比增长(%)指数月度数据分析与对比\n",
    "#### 分省固定资产投资完成额累积增长和工业增加值的同比增长，可以从一个侧面反映出我们的工业增加值是否有一个稳定且增长的势头。在经济学当中，经常讲到的是投资加速器效应，也就是说，如果固定资产的投资在某个月出现大幅的增长，那么其工业增加值也会在后续的月份出现同比增长，并且会在一段时间后产生更明显的投资加速器效应。从我们的分析看出，在2019年3月份的分省固定资产投资完成额累计增长和2019年8月份工业增加值同比增长的对比，可以看出，我国的大部分省份都完美验证了这一理论的实践正确性，同时也说明了我国的经济增长地基非常的扎实，经济依然会在一个稳中向好的环境发展，不会出现大幅的经济波动情况。"
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